The incidence of oxygen desaturation during rapid sequence induction and intubation

BACKGROUND: Rapid sequence induction and intubation(RSII) is an emergency airway management technique for patients with a risk of pulmonary aspiration. It involves preoxygenation, administration of predetermined doses of induction and paralytic drugs, avoidance of mask ventilation, and laryngoscopy followed by tracheal intubation and keeping cricoid pressure applied till endotracheal tube cuff be inflated. Oxygen desaturation has been seen during RSII. We assessed the incidence of oxygen desaturation during RSII.METHODS: An institution-based observational study was conducted from March 3 to May 4, 2014 in our hospital. All patients who were operated upon under general anesthesia with RSII during the study period were included. A checklist was prepared for data collection.RESULTS: A total of 153 patients were included in this study with a response rate of 91.6%. Appropriate drugs for RSII, equipments for RSII, equipments for diffi cult intubation, suction machine with a catheter, a monitor and an oxygen backup such as ambu bag were not prepared for 41(26.8%), 50(32.7%), 51(33.3%), 38(24.8%) and 25(16.3%) patients respectively. Cricoid pressure was not applied at all for 17(11.1%) patients and 53(34.6%) patients were ventilated after induction of anesthesia but before intubation and endotracheal cuff inflation. A total of 55(35.9%) patients desaturated during RSII(SPO2<95%). The minimum, maximum and mean oxygen desaturations were 26%, 94% and 70.9% respectively. The oxygen desaturation was in the range of <50%, 50%–64%, 65%–74%, 75%–84%, 85%–89 % and 90%–94% for 6(3.9%), 7(4.6%), 5(3.3%), 10(6.5%), 13(8.5%) and 14(9.2%) patients respectively.CONCLUSION: The incidence of oxygen desaturation during RSII was high in our hospital. Preoperative patient optimization and training about the techniques of RSII should be emphasized.

An Improved Encoder-Decoder CNN with Region-Based Filtering for Vibrant Colorization

Colorization is the practice of adding appropriate chromatic values to monochrome photographs or videos.A real-valued luminance image can be mapped to a three-dimensional color image.However,it is a severely ill-defined problem and not has a single solution.In this paper,an encoder-decoder Convolutional Neural Network(CNN)model is used for colorizing gray images where the encoder is a Densely Connected Convolutional Network(DenseNet)and the decoder is a conventional CNN.The DenseNet extracts image features from gray images and the conventional CNN outputs a^(*)b^(*)color channels.Due to a large number of desaturated color components compared to saturated color components in the training images,the saturated color components have a strong tendency towards desaturated color components in the predicted a^(*)b^(*)channel.To solve the problems,we rebalance the predicted a^(*)b^(*)color channel by smoothing every subregion individually using the average filter.2 stage k-means clustering technique is applied to divide the subregions.Then we apply Gamma transformation in the entire a^(*)b^(*)channel to saturate the image.We compare our proposed method with several existing methods.From the experimental results,we see that our proposed method has made some notable improvements over the existing methods and color representation of gray-scale images by our proposed method is more plausible to visualize.Additionally,our suggested approach beats other approaches in terms of Peak Signal-to-Noise Ratio(PSNR),Structural Similarity Index Measure(SSIM)and Histogram.

Sleep disordered breathing in coronary heart disease patients with mild and moderate heart failure

The purpose of the study was to investigate the relationship between sleep disordered breathing (SDB) and degree of heart failure (HF) in patients with coronary heart disease (CHD). A total of 3017 patients (77.4% men and 22.6% women) were included in the study. Clinical examination and echocardiography for evaluation of HF using NYHA functional classification and sleep polysomnography were performed. The study demonstrated that SDB is more common in CHD patients with higher NYHA functional class. The prevalence of central sleep apneas against obstructive apneas was observed in patients with mild and moderate HF. The number of central apneas was strongly related to the severity of heart failure. More frequent appearance of central sleep apneas is predominantly due to instability of ventilatory control systems during sleep because of impaired cardiac function in HF patients. Sleep architecture was more disturbed in CHD patients with higher NYHA functional class. A gradual increase of stage 1 and wakefulness after sleep onset and a decrease of sleep stages 3-4 and REM sleep as well as a diminution of sleep efficiency with worsening of NYHA functional class were observed. We suggest that both SDB and disturbed sleep variables independently significantly correlate with manifestation of HF.

Correlation between obstructive sleep apnea and central retinal vein occlusion

To investigate the possible correlation between obstructive sleep apnea(OSA) and central retinal vein occlusion(CRVO). Thirty consecutive patients with a recent(<3 mo)CRVO and an age-and sex-matched group of 30 control subjects were recruited. All subjects underwent full-night polysomnography to measure apnea-hypopnea index(AHI)and oxygen desaturation index(ODI). The average AHI and ODI were significantly higher in CRVO patients(AHI:13.86±8.63, ODI: 9.21±4.47) than in control subjects(AHI:8.51±6.36, ODI: 5.87±3.18;P=0.008 and 0.001 respectively).Additionally, the AHI was positively correlated with body mass index(BMI;r=0.476, P=0.017) and ODI(r=0.921,P<0.01) in both CRVO and control subjects. According to AHI scores, twenty-two(73.33%) CRVO patients had OSA and 12(40.00%) control subjects had OSA, a difference that was statistically significant(P=0.019). OSA may be a risk factor for or a trigger of CRVO development.